Knowledge-guided convolutional networks for chemical-disease relation extraction.

Journal: BMC bioinformatics
Published Date: May 21, 2019

Abstract

BACKGROUND: Automatic extraction of chemical-disease relations (CDR) from unstructured text is of essential importance for disease treatment and drug development. Meanwhile, biomedical experts have built many highly-structured knowledge bases (KBs), which contain prior knowledge about chemicals and diseases. Prior knowledge provides strong support for CDR extraction. How to make full use of it is worth studying.

Authors

  • Huiwei Zhou
    School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, China.
  • Chengkun Lang
    School of Computer Science and Technology, Dalian University of Technology, Chuangxinyuan Building, No. 2 Linggong Road, Ganjingzi District, Dalian, Liaoning, China.
  • Zhuang Liu
    Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
  • Shixian Ning
    School of Computer Science and Technology, Dalian University of Technology, Chuangxinyuan Building, No. 2 Linggong Road, Ganjingzi District, Dalian, Liaoning, China.
  • Yingyu Lin
    School of Foreign Languages, Dalian University of Technology, Arts Building, No. 2 Linggong Road, Ganjingzi District, Dalian, Liaoning, China.
  • Lei Du
    School of Mathematical Sciences, Dalian University of Technology, Chuangxinyuan Building, No.2 Linggong Road, Ganjingzi District, Dalian, 116024, Liaoning, China.

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